100% RETURN ON AD SPEND WITHIN 7 DAYS FOR ATARI’S ROLLERCOASTER TYCOON® TOUCH
Launching Roller Coaster Tycoon Touch
At launch, RollerCoaster Tycoon Touch (RCTT) achieved Top 1 Overall rank in the iOS App Store and maintained that position for the first week. RCTT reached 7.5 Million downloads on Android and iOS in the first 100 days.
GameChangerSF had been working with Atari for over two years on the other mobile titles. Atari and GameChangerSF defined the launch strategy and its execution for RollerCoaster Tycoon Touch.
After a big launch and featuring by Apple, the growth of Atari's DAU (daily active users) started to reach a limit. Atari and GameChangerSF aimed at stabilizing DAU above 300,000 and growing the user base and total revenue from there. Positive return on the ad spend (ROAS) was an absolute requirement from day one.
Results exceeded Atari's initial objectives:
800,000+ users acquired within three months for under
The revenue from users acquired exceeded the cost.
DAU is starting to grow again thanks to paid users who generated an increasing share of the overall revenue. Payback period went from 60 days atlaunch to 30 days and finally to 7-14 days; with 7-day ROAS reaching 100% at the time of this study, on an increasing scale.
7 Day Return on Ad Spend
HOW ATARI AND GAMECHANGERSF DID IT
The key to the success is the tactic that we called “geo-arbitrage” – frequent rotation of countries in the acquisition mix to optimize for audiences with the highest conversion, while letting depleting audiences rest.
In the first two months, US and UK accounted for 80% of the marketing spend and 90% of revenue from paid users. Later, a large portion of the spend was shifted to Europe, putting some of the most valuable Tier 1 audiences “on ice” until they refreshed.
More recently, less than a third of paid users came from US and UK, with more users coming from South America with a superior profit margin. Similar good results were seen with certain countries in South East Asia.
Finding monetizing users in Tier 3 countries in not easy. The search relies on proprietary data, audience intelligence and bidding algorithms to find users with a high likelihood of becoming big spenders.